Ngawha Reservoir ModelJohn Burnell
JOGMEC-GNS Workshop, Tokyo
2 June 2016

GNS ScienceOutline• Purpose• Conceptual Model• Model Structure• Model Verification• Expansion Scenario• Surface Features Model

Slide 2GNS SciencePurpose• To develop a numerical reservoir model of theNgawha Geothermal Field for consentingpurposes• Objectives– Obtain an acceptable match to historical data
– Use a dual porosity model to more accurately model
injection returns in the reservoir– Consider effects of possible future expansion– Predict impact on surface features

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GNS ScienceConceptual Model

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GNS ScienceReservoir Characteristics• Reservoir hosted in Waipapa Greywacke
between 500m and 1500m depth– Low porosity– Permeability due to fractures and faults• Low permeability siltstones form a cap– Some transport through faults and fractures

Slide 5GNS ScienceResource AreasOperations
area

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GNS ScienceReservoir Characteristics II• Geology– Permeable greywacke– Cap with small channels connecting to surface• Temperatures in permeable reservoir are ~230 °C• Hotter temperatures in the north• Pre-production testing suggested fractured
reservoir with high permeability• Hot upflow > 300°C, located in north < 10 kg/s
• CO2 concentrations ~1.5%

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GNS ScienceHydrological Model

Slide 8GNS Science

Model Validation Data
• Pre-production temperature and pressure
measurements.
• Measured changes in reservoir pressure due toproduction.
• Changes in production enthalpies.
• Changes in CO2 concentrations in production
wells.
• Measured pressure changes in the 1983
interference tests.
• Travel times from the 2011 tracer test.
Slide 9GNS ScienceDual Porosity Numerical Reservoir Model

Slide 10GNS ScienceDual Porosity ModelUsed to represent flows in fractures• Fast flow paths• Small volumes• Model coolingMatrix

Fracture

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GNS Science

Model Grid

Slide 12GNS ScienceGeology and Resource Boundary

Permeable innerregion

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GNS ScienceUpflow
Upflow =10 kg/s

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GNS Science

Model Verification

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GNS ScienceMethodology• Run natural state model– Compare to measured temperatures and pressures• Run historical production– Compare to measured pressure changes, enthalpies
and CO2 concentrations• Add tracer injection.
– Compare to measured tracer• Run production and injection for 1983
interference test
– Compare to measured pressures
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GNS ScienceNatural State Temperatures

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GNS ScienceSlide 18

GNS ScienceSome Improvements Still Needed

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GNS ScienceNatural State Pressures

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GNS ScienceChanges Due to Development

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GNS ScienceSlide 22

GNS Science

Pressures in Injectors Don't Match as Well

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GNS ScienceProduction Enthalpies

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GNS ScienceSlide 25

GNS ScienceSlide 26

GNS ScienceIssues with Enthalpies• Inconsistent with measured tempertures– NG9 temperatures give enthalpies of 980 kJ/kg– Initial data – 920 kJ/kg– Also inconsistency between well enthalpies andstation enthalpies– In other fields it is suggested that measurement
uncertainties are ~100 kJ/kg– If this is the case then the model agrees within
measurement uncertainty.

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GNS ScienceSlide 28

GNS ScienceCO2 Concentration• CO2 gives information about long term
connection between injectors and producers

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GNS ScienceSlide 30

GNS ScienceSlide 31

GNS ScienceTracer Test – Injection into NG16
• Arrival times give information about short termtransport between injectors and producers
NG16 Tracer
4.5
4Concentration (ug/L)

3.5
3
2.5
NG42NG91.5NG1210.50

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GNS Science

Model Results

Arrivaltime

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GNS ScienceSlide 34

GNS Science

Interference Test – October 1983
• Pressure propagation across the reservoir

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GNS ScienceOverall Match• Ngawha Numerical Reservoir Model is wellcalibrated• Matches data from many different aspects of thefield• Based on physical understanding– Reduces uncertainty

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GNS Science

Expansion Scenarios

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GNS Science

Expansion Scenarios• Two scenarios– Scenario A: 25 MWe expansion– Scenario B: 50 MWe expansion• 25 MWe stage from 2020
• 50 MWe stage from 2023

• Adjusted injection rates to match observations– Loss of gases (currently 0.5%)– Other loses/spillages (0.35%)• Used supplemental injection to control reservoirpressures
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GNS ScienceScenario Pressures

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GNS ScienceSome pressure changes

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GNS ScienceEnthalpies Decline

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GNS Science

Will need some plant changes

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GNS ScienceSurface Feature Modelling

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GNS ScienceSurface Feature Modelling• Ngawha Springs are valued highly by localcommunity• Ngawha Springs have low flow rates• Reservoir model is too coarse to capturechanges in flow to surface features• Developed a separate model of the area aroundthe surface features

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GNS ScienceSchematic of Surface Feature Model

Surface Waters

PermeableConduitCaprock

Deep Reservoir

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GNS Science

Model Grid

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GNS Science

Vertical Extent

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GNS ScienceNatural State Temperatures

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GNS ScienceNatural State Pressures

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GNS ScienceSurface Feature Model Setup• Fixed pressures and temperatures in the bottom
boundary– Corresponding to measured reservoir data

• Fixed conditions in atmosphere• Flow driven by boundary conditions– Adjust conduit permeability to match flow
– Modelled flow was 1.3 kg/s

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GNS ScienceResponse to Production• Used output from numerical reservoir modelexpansion scenario– Reduced reservoir pressure by 0.3 bar– Reduced reservoir temperature by 1 °C
– Reduced reservoir CO2 mass fraction from 1.3% to0.1%

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GNS ScienceSurface Feature Model Results – Flow toSurface

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GNS ScienceSurface Feature Model Results – SteamFraction

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GNS ScienceSurface Feature Model Results – Temperature

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GNS ScienceSurface Feature Model Results – CO2 inDischargeSlide 55

GNS ScienceChemistry Calculation for Surface Features• Ran a calculation with GeoChemist Workbench
to obtain spring chemistry• Reduced the CO2 content and re-calculated• The main changes are an increase in pH (6.2 =>6.95) and a reduction in HCO3-.

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GNS Science

Conclusions• Well-calibrated model for consenting purposes• Matches many different aspects of flow in thereservoir• Pressures can be controlled for 50 MWe
expansion scenario• Impact on surface features is minor

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GNS Science